wrapper tools to help the user: scale2frequency, frequency2scale, show_wavelet

[jerabaul29]

If I understand well, a critical aspect of using the wavelet transform is to i) choose the correct scales, ii) choose appropriate wavelets. I use this page as a reference when doing so: https://pywavelets.readthedocs.io/en/latest/ref/cwt.html . At first, it was a bit confusing. I wonder if it would be possible to:

• extend the pywt.scale2frequency function signature by adding a sampling_frequency=1 parameter, so that the user does not need to perform the /dt to get to the real world frequency
• also provide a "reciprocal" function, i.e. pywt.frequency2scale(wavelet, list_frequencies, sampling_frequency) that will provide the scales to use directly from the frequencies that the user thinks are useful; this way, the user will not have to go through the hurdle of inverting the pywt.scale2frequency function themselves
• update https://pywavelets.readthedocs.io/en/latest/ref/cwt.html with these new "simpler ways to use"
• provide a simple way to plot wavelets, i.e. pywt.plot_wavelet(wavelet, scale, sampling_frequency), that will plot the wavelet as a function of time
• show a plot for each of the wavelets in https://pywavelets.readthedocs.io/en/latest/ref/cwt.html

[tkuraku]

+1 on the frequency2scale function. That would make it easier to have a uniform frequency sampling in the transform.

[grlee77]

This was partially resolved by #635, which added frequency2scale